Monday, 31 October 2016
Top 5 Programming Languages thats gives you fat salaries.
C Language
C (/ˈsiː/, as in the letter c) is a general-purpose, imperative computer programming language, supporting structured programming, lexical variable scope and recursion, while a static type system prevents many unintended operations. By design, C provides constructs that map efficiently to typical machine instructions, and therefore it has found lasting use in applications that had formerly been coded in assembly language, including operating systems, as well as various application software for computers ranging from supercomputers to embedded systems.C was originally developed by Dennis Ritchie between 1969 and 1973 at Bell Labs,[5] and used to re-implement the Unix operating system.[6] It has since become one of the most widely used programming languages of all time,[7][8] with C compilers from various vendors available for the majority of existing computer architectures and operating systems. C has been standardized by the American National Standards Institute (ANSI) since 1989 (see ANSI C) and subsequently by the International Organization for Standardization (ISO).
Java
This article is about a programming language. For the software package downloaded from java.com, see Java SE.
Not to be confused with JavaScript.
Java Java programming language logo.svg
Paradigm Multi-paradigm: Object-oriented (class-based), structured, imperative, generic, reflective, concurrent
Designed by James Gosling
Developer Sun Microsystems (now owned by Oracle Corporation)
First appeared May 23, 1995; 21 years ago[1]
Typing discipline Static, strong, safe, nominative, manifest
License GNU General Public License, Java Community Process
Filename extensions .java , .class, .jar
Website www.oracle.com/java/
Major implementations
OpenJDK, GNU Compiler for Java (GCJ), many others
Dialects
Generic Java, Pizza
Influenced by
Ada 83, C++,[2] C#,[3] Eiffel,[4] Generic Java, Mesa,[5] Modula-3,[6] Oberon,[7] Objective-C,[8] UCSD Pascal,[9][10] Object Pascal[11]
Influenced
Ada 2005, BeanShell, C#, Chapel,[12] Clojure, ECMAScript, Fantom, Groovy, Hack,[13] Haxe, J#, JavaScript, Kotlin, PHP, Python, Scala, Seed7, Vala
Java Programming at Wikibooks
Java is a general-purpose computer programming language that is concurrent, class-based, object-oriented,[14] and specifically designed to have as few implementation dependencies as possible. It is intended to let application developers "write once, run anywhere" (WORA),[15] meaning that compiled Java code can run on all platforms that support Java without the need for recompilation.[16] Java applications are typically compiled to bytecode that can run on any Java virtual machine (JVM) regardless of computer architecture. As of 2016, Java is one of the most popular programming languages in use,[17][18][19][20] particularly for client-server web applications, with a reported 9 million developers.[21] Java was originally developed by James Gosling at Sun Microsystems (which has since been acquired by Oracle Corporation) and released in 1995 as a core component of Sun Microsystems' Java platform. The language derives much of its syntax from C and C++, but it has fewer low-level facilities than either of them.
The original and reference implementation Java compilers, virtual machines, and class libraries were originally released by Sun under proprietary licences. As of May 2007, in compliance with the specifications of the Java Community Process, Sun relicensed most of its Java technologies under the GNU General Public License. Others have also developed alternative implementations of these Sun technologies, such as the GNU Compiler for Java (bytecode compiler), GNU Classpath (standard libraries), and IcedTea-Web (browser plugin for applets).
The latest version is Java 8, which is the only version currently supported for free by Oracle, although earlier versions are supported both by Oracle and other companies on a commercial basis.
C++
C++ (pronounced cee plus plus, /ˈsiː plʌs plʌs/) is a general-purpose programming language. It has imperative, object-oriented and generic programming features, while also providing facilities for low-level memory manipulation.
It was designed with a bias toward system programming and embedded, resource-constrained and large systems, with performance, efficiency and flexibility of use as its design highlights.[5] C++ has also been found useful in many other contexts, with key strengths being software infrastructure and resource-constrained applications,[5] including desktop applications, servers (e.g. e-commerce, web search or SQL servers), and performance-critical applications (e.g. telephone switches or space probes).[6] C++ is a compiled language, with implementations of it available on many platforms and provided by various organizations, including the Free Software Foundation (FSF's GCC), LLVM, Microsoft, Intel and IBM.
C++ is standardized by the International Organization for Standardization (ISO), with the latest standard version ratified and published by ISO in December 2014 as ISO/IEC 14882:2014 (informally known as C++14).[7] The C++ programming language was initially standardized in 1998 as ISO/IEC 14882:1998, which was then amended by the C++03, ISO/IEC 14882:2003, standard. The current C++14 standard supersedes these and C++11, with new features and an enlarged standard library. Before the initial standardization in 1998, C++ was developed by Bjarne Stroustrup at Bell Labs since 1979, as an extension of the C language as he wanted an efficient and flexible language similar to C, which also provided high-level features for program organization.
Many other programming languages have been influenced by C++, including C#, D, Java, and newer versions of C (after 1998).
It was designed with a bias toward system programming and embedded, resource-constrained and large systems, with performance, efficiency and flexibility of use as its design highlights.[5] C++ has also been found useful in many other contexts, with key strengths being software infrastructure and resource-constrained applications,[5] including desktop applications, servers (e.g. e-commerce, web search or SQL servers), and performance-critical applications (e.g. telephone switches or space probes).[6] C++ is a compiled language, with implementations of it available on many platforms and provided by various organizations, including the Free Software Foundation (FSF's GCC), LLVM, Microsoft, Intel and IBM.
C++ is standardized by the International Organization for Standardization (ISO), with the latest standard version ratified and published by ISO in December 2014 as ISO/IEC 14882:2014 (informally known as C++14).[7] The C++ programming language was initially standardized in 1998 as ISO/IEC 14882:1998, which was then amended by the C++03, ISO/IEC 14882:2003, standard. The current C++14 standard supersedes these and C++11, with new features and an enlarged standard library. Before the initial standardization in 1998, C++ was developed by Bjarne Stroustrup at Bell Labs since 1979, as an extension of the C language as he wanted an efficient and flexible language similar to C, which also provided high-level features for program organization.
Many other programming languages have been influenced by C++, including C#, D, Java, and newer versions of C (after 1998).
Python
Python is a widely used high-level, general-purpose, interpreted, dynamic programming language.[24][25] Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java.[26][27] The language provides constructs intended to enable writing clear programs on both a small and large scale.[28]
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.[29]
Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller,[30] Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, so Python-based software can be distributed to, and used on, those environments with no need to install a Python interpreter.
CPython, the reference implementation of Python, is free and open-source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.[29]
Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller,[30] Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, so Python-based software can be distributed to, and used on, those environments with no need to install a Python interpreter.
CPython, the reference implementation of Python, is free and open-source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.
Hadoop
Apache Hadoop (pronunciation: /həˈduːp/) is an open-source software framework for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common and should be automatically handled by the framework.[2]
The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called MapReduce. Hadoop splits files into large blocks and distributes them across nodes in a cluster. To process data, Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed. This approach takes advantage of data locality[3] – nodes manipulating the data they have access to – to allow the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking.[4]
The base Apache Hadoop framework is composed of the following modules:
Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN – a resource-management platform responsible for managing computing resources in clusters and using them for scheduling of users' applications;[5][6] and
Hadoop MapReduce – an implementation of the MapReduce programming model for large scale data processing.
The term Hadoop has come to refer not just to the base modules above, but also to the ecosystem,[7] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, Apache Storm.[8]
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on their MapReduce and Google File System.[9]
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with "Hadoop Streaming" to implement the "map" and "reduce" parts of the user's program.[10] Other projects in the Hadoop ecosystem expose richer user interfaces.
The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called MapReduce. Hadoop splits files into large blocks and distributes them across nodes in a cluster. To process data, Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed. This approach takes advantage of data locality[3] – nodes manipulating the data they have access to – to allow the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking.[4]
The base Apache Hadoop framework is composed of the following modules:
Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN – a resource-management platform responsible for managing computing resources in clusters and using them for scheduling of users' applications;[5][6] and
Hadoop MapReduce – an implementation of the MapReduce programming model for large scale data processing.
The term Hadoop has come to refer not just to the base modules above, but also to the ecosystem,[7] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, Apache Storm.[8]
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on their MapReduce and Google File System.[9]
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with "Hadoop Streaming" to implement the "map" and "reduce" parts of the user's program.[10] Other projects in the Hadoop ecosystem expose richer user interfaces.
Top 5 Programming Languages thats gives you fat salaries.
C Language
C (/ˈsiː/, as in the letter c) is a general-purpose, imperative computer programming language, supporting structured programming, lexical variable scope and recursion, while a static type system prevents many unintended operations. By design, C provides constructs that map efficiently to typical machine instructions, and therefore it has found lasting use in applications that had formerly been coded in assembly language, including operating systems, as well as various application software for computers ranging from supercomputers to embedded systems.C was originally developed by Dennis Ritchie between 1969 and 1973 at Bell Labs,[5] and used to re-implement the Unix operating system.[6] It has since become one of the most widely used programming languages of all time,[7][8] with C compilers from various vendors available for the majority of existing computer architectures and operating systems. C has been standardized by the American National Standards Institute (ANSI) since 1989 (see ANSI C) and subsequently by the International Organization for Standardization (ISO).
Java
This article is about a programming language. For the software package downloaded from java.com, see Java SE.
Not to be confused with JavaScript.
Java Java programming language logo.svg
Paradigm Multi-paradigm: Object-oriented (class-based), structured, imperative, generic, reflective, concurrent
Designed by James Gosling
Developer Sun Microsystems (now owned by Oracle Corporation)
First appeared May 23, 1995; 21 years ago[1]
Typing discipline Static, strong, safe, nominative, manifest
License GNU General Public License, Java Community Process
Filename extensions .java , .class, .jar
Website www.oracle.com/java/
Major implementations
OpenJDK, GNU Compiler for Java (GCJ), many others
Dialects
Generic Java, Pizza
Influenced by
Ada 83, C++,[2] C#,[3] Eiffel,[4] Generic Java, Mesa,[5] Modula-3,[6] Oberon,[7] Objective-C,[8] UCSD Pascal,[9][10] Object Pascal[11]
Influenced
Ada 2005, BeanShell, C#, Chapel,[12] Clojure, ECMAScript, Fantom, Groovy, Hack,[13] Haxe, J#, JavaScript, Kotlin, PHP, Python, Scala, Seed7, Vala
Java Programming at Wikibooks
Java is a general-purpose computer programming language that is concurrent, class-based, object-oriented,[14] and specifically designed to have as few implementation dependencies as possible. It is intended to let application developers "write once, run anywhere" (WORA),[15] meaning that compiled Java code can run on all platforms that support Java without the need for recompilation.[16] Java applications are typically compiled to bytecode that can run on any Java virtual machine (JVM) regardless of computer architecture. As of 2016, Java is one of the most popular programming languages in use,[17][18][19][20] particularly for client-server web applications, with a reported 9 million developers.[21] Java was originally developed by James Gosling at Sun Microsystems (which has since been acquired by Oracle Corporation) and released in 1995 as a core component of Sun Microsystems' Java platform. The language derives much of its syntax from C and C++, but it has fewer low-level facilities than either of them.
The original and reference implementation Java compilers, virtual machines, and class libraries were originally released by Sun under proprietary licences. As of May 2007, in compliance with the specifications of the Java Community Process, Sun relicensed most of its Java technologies under the GNU General Public License. Others have also developed alternative implementations of these Sun technologies, such as the GNU Compiler for Java (bytecode compiler), GNU Classpath (standard libraries), and IcedTea-Web (browser plugin for applets).
The latest version is Java 8, which is the only version currently supported for free by Oracle, although earlier versions are supported both by Oracle and other companies on a commercial basis.
C++
C++ (pronounced cee plus plus, /ˈsiː plʌs plʌs/) is a general-purpose programming language. It has imperative, object-oriented and generic programming features, while also providing facilities for low-level memory manipulation.
It was designed with a bias toward system programming and embedded, resource-constrained and large systems, with performance, efficiency and flexibility of use as its design highlights.[5] C++ has also been found useful in many other contexts, with key strengths being software infrastructure and resource-constrained applications,[5] including desktop applications, servers (e.g. e-commerce, web search or SQL servers), and performance-critical applications (e.g. telephone switches or space probes).[6] C++ is a compiled language, with implementations of it available on many platforms and provided by various organizations, including the Free Software Foundation (FSF's GCC), LLVM, Microsoft, Intel and IBM.
C++ is standardized by the International Organization for Standardization (ISO), with the latest standard version ratified and published by ISO in December 2014 as ISO/IEC 14882:2014 (informally known as C++14).[7] The C++ programming language was initially standardized in 1998 as ISO/IEC 14882:1998, which was then amended by the C++03, ISO/IEC 14882:2003, standard. The current C++14 standard supersedes these and C++11, with new features and an enlarged standard library. Before the initial standardization in 1998, C++ was developed by Bjarne Stroustrup at Bell Labs since 1979, as an extension of the C language as he wanted an efficient and flexible language similar to C, which also provided high-level features for program organization.
Many other programming languages have been influenced by C++, including C#, D, Java, and newer versions of C (after 1998).
It was designed with a bias toward system programming and embedded, resource-constrained and large systems, with performance, efficiency and flexibility of use as its design highlights.[5] C++ has also been found useful in many other contexts, with key strengths being software infrastructure and resource-constrained applications,[5] including desktop applications, servers (e.g. e-commerce, web search or SQL servers), and performance-critical applications (e.g. telephone switches or space probes).[6] C++ is a compiled language, with implementations of it available on many platforms and provided by various organizations, including the Free Software Foundation (FSF's GCC), LLVM, Microsoft, Intel and IBM.
C++ is standardized by the International Organization for Standardization (ISO), with the latest standard version ratified and published by ISO in December 2014 as ISO/IEC 14882:2014 (informally known as C++14).[7] The C++ programming language was initially standardized in 1998 as ISO/IEC 14882:1998, which was then amended by the C++03, ISO/IEC 14882:2003, standard. The current C++14 standard supersedes these and C++11, with new features and an enlarged standard library. Before the initial standardization in 1998, C++ was developed by Bjarne Stroustrup at Bell Labs since 1979, as an extension of the C language as he wanted an efficient and flexible language similar to C, which also provided high-level features for program organization.
Many other programming languages have been influenced by C++, including C#, D, Java, and newer versions of C (after 1998).
Python
Python is a widely used high-level, general-purpose, interpreted, dynamic programming language.[24][25] Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java.[26][27] The language provides constructs intended to enable writing clear programs on both a small and large scale.[28]
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.[29]
Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller,[30] Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, so Python-based software can be distributed to, and used on, those environments with no need to install a Python interpreter.
CPython, the reference implementation of Python, is free and open-source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.[29]
Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller,[30] Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, so Python-based software can be distributed to, and used on, those environments with no need to install a Python interpreter.
CPython, the reference implementation of Python, is free and open-source software and has a community-based development model, as do nearly all of its variant implementations. CPython is managed by the non-profit Python Software Foundation.
Hadoop
Apache Hadoop (pronunciation: /həˈduːp/) is an open-source software framework for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common and should be automatically handled by the framework.[2]
The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called MapReduce. Hadoop splits files into large blocks and distributes them across nodes in a cluster. To process data, Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed. This approach takes advantage of data locality[3] – nodes manipulating the data they have access to – to allow the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking.[4]
The base Apache Hadoop framework is composed of the following modules:
Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN – a resource-management platform responsible for managing computing resources in clusters and using them for scheduling of users' applications;[5][6] and
Hadoop MapReduce – an implementation of the MapReduce programming model for large scale data processing.
The term Hadoop has come to refer not just to the base modules above, but also to the ecosystem,[7] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, Apache Storm.[8]
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on their MapReduce and Google File System.[9]
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with "Hadoop Streaming" to implement the "map" and "reduce" parts of the user's program.[10] Other projects in the Hadoop ecosystem expose richer user interfaces.
The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called MapReduce. Hadoop splits files into large blocks and distributes them across nodes in a cluster. To process data, Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed. This approach takes advantage of data locality[3] – nodes manipulating the data they have access to – to allow the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking.[4]
The base Apache Hadoop framework is composed of the following modules:
Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN – a resource-management platform responsible for managing computing resources in clusters and using them for scheduling of users' applications;[5][6] and
Hadoop MapReduce – an implementation of the MapReduce programming model for large scale data processing.
The term Hadoop has come to refer not just to the base modules above, but also to the ecosystem,[7] or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Cloudera Impala, Apache Flume, Apache Sqoop, Apache Oozie, Apache Storm.[8]
Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on their MapReduce and Google File System.[9]
The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with "Hadoop Streaming" to implement the "map" and "reduce" parts of the user's program.[10] Other projects in the Hadoop ecosystem expose richer user interfaces.
Maisi Williams sexy video leaked
Williams has also had a recurring role in Doctor Who as Ashildr in 2015. In addition to television, she made her feature film debut in the mystery The Falling, for which she won the London Film Critics' Circle Award for Young Performer of the Year.
Early life
Williams was born in Bristol, UK.[3][4] She has always been known as "Maisie" after the character from the comic strip The Perishers.[5] Williams is the youngest of four children; her three older siblings are James, Beth and Ted.[5] Born to Hilary Pitt (now Frances),[6] a former university course administrator, she grew up in Clutton, Somerset.[4][7] She attended Clutton Primary School and Norton Hill School in Midsomer Norton, before moving to Bath Dance College to study Performing Arts.[8][9]
Maisie Williams/Arya Stark Sex Scene - The Falling
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